Track 2-8-1: Impact of Market Demands on Grassland Management and Livestock Husbandry
Description
Sustainable management of Australia’s extensive northern grazing lands is challenging given its highly variable interannual rainfall and pasture production. Accordingly, a key management recommendation is to adjust stocking rates to match forage supply (O’Reagain et al., 2014). ‘Stocktake’ is a forage budgeting system (Aisthorpe et al., 2004) widely used and promoted to assist graziers make short-term (< 1 year) adjustments of stocking rate. Budgets are typically calculated at the start of the dry season, to ensure sufficient forage for stock and ground cover levels until the first rains some six to nine months later. The software application ‘Future Beef Stocktake Plus’ has also been developed for use on smart devices (http://www.stocktakeplus.com.au/).
A key requirement for forage budgets is an accurate estimate of pasture mass. This is typically done visually with the aid of photo standards of pasture mass, providing a simple, efficient and non-destructive approach. Other key variables of forage budgeting include the percent of the pasture not likely to be consumed by livestock (i.e. percent unpalatable) and pasture wastage that occurs as a result of trampling, decay, leaf drop and consumption by insects. Despite adoption of the Stocktake forage budget system by graziers, key variables do not appear to have been investigated and uncertainty exists on the accuracy of pasture yield estimates. Accordingly, the degree of error, operator variability and the potential impact of factors such as land type and starting yield on yield estimates and hence, calculated stocking rates, are unknown. This study examined operator bias associated with the visual assessment of pasture total standing dry matter (TSDM) using photo standards and the extent to which this bias was affected by operator, land type and starting yield. The effect of training on operator yield assessments was also investigated.
Citation
Spiegel, Nicole B.; O'Reagin, Peter; Anderson, Angela; and Willis, Megan R., "Operator Bias and the Effect of Training on Visual Assessments of Pasture Yield for Forage Budgets in Northern Australian Savanna" (2020). IGC Proceedings (1993-2023). 9.
https://uknowledge.uky.edu/igc/23/2-8-1/9
Included in
Operator Bias and the Effect of Training on Visual Assessments of Pasture Yield for Forage Budgets in Northern Australian Savanna
Sustainable management of Australia’s extensive northern grazing lands is challenging given its highly variable interannual rainfall and pasture production. Accordingly, a key management recommendation is to adjust stocking rates to match forage supply (O’Reagain et al., 2014). ‘Stocktake’ is a forage budgeting system (Aisthorpe et al., 2004) widely used and promoted to assist graziers make short-term (< 1 year) adjustments of stocking rate. Budgets are typically calculated at the start of the dry season, to ensure sufficient forage for stock and ground cover levels until the first rains some six to nine months later. The software application ‘Future Beef Stocktake Plus’ has also been developed for use on smart devices (http://www.stocktakeplus.com.au/).
A key requirement for forage budgets is an accurate estimate of pasture mass. This is typically done visually with the aid of photo standards of pasture mass, providing a simple, efficient and non-destructive approach. Other key variables of forage budgeting include the percent of the pasture not likely to be consumed by livestock (i.e. percent unpalatable) and pasture wastage that occurs as a result of trampling, decay, leaf drop and consumption by insects. Despite adoption of the Stocktake forage budget system by graziers, key variables do not appear to have been investigated and uncertainty exists on the accuracy of pasture yield estimates. Accordingly, the degree of error, operator variability and the potential impact of factors such as land type and starting yield on yield estimates and hence, calculated stocking rates, are unknown. This study examined operator bias associated with the visual assessment of pasture total standing dry matter (TSDM) using photo standards and the extent to which this bias was affected by operator, land type and starting yield. The effect of training on operator yield assessments was also investigated.
